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# cube aligned
import ndio.remote.neurodata as neurodata
from time import time
import numpy as np
import ndparse as ndp

# slice
start = time()
nd = neurodata(chunk_size=1e5)
xy = nd.get_xy_slice('kasthuri11cc','image',4096,4096+1024,4096,4096+1024,1,resolution=1)

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addpath(genpath('TREES1.15'))
start_trees

files = dir('*.swc');
for i = 1:length(files)
trees{i} = load_tree(files(i).name);
end

for i = 1:length(trees) 
    try 

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NeuroData HPC (v0.1)

W. Gray Roncal &c

Current Strategy

Our current approach is to divide workflows into labeling, train, evaluate, and deploy.

The tools for processing exist in a variety of languages and frameworks, but these are the predominant use-cases.

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import glob
import os
import matplotlib.pyplot as plt
import matplotlib.image as mpimg
import numpy as np
import ndio.remote.OCP as OCP

dir = '/Users/graywr1/Downloads/temp'
os.chdir(dir)

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%% for Sandra
im = imread('~/Downloads/mGCaMP3 IEM SomatosensoryCx-bottom.jpg');
%experiment until you're happy
figure, imagesc(im<40)
it = im < 40;

itd = imdilate(it, strel('disk', 15));
figure, imagesc(itd)

rp = regionprops(itd,'PixelIdxList','Area');

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function ocp_upload_voxelList(server, token, RAMONVolume, protoRAMON, useSemaphore)

% W. Gray Roncal

% Function to upload objects in a RAMON volume as a voxelList

% Requires that all objects begin from a common prototype, and that
% RAMONVolume has appropriate fields (in particular resolution and XYZ
% offset)
% This only supports anno32 data for now and the preserve anno option

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function metrics = pr_eval(detectVol, truthVol)
% W. Gray Roncal - 02.12.2015 
% Feedback welcome and encouraged.  Let's make this better!
% Other options (size filters, morphological priors, etc. can be added.
% z = rand(100,100);
% t = z > 0.8;
%
tic

%% params

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% Updated to channel conventions and data migrations as of 01.24.2016
% Demonstrates downloading from the server and uploading from the server (best practices)		
% W. Gray Roncal
% Assumes CAJAL is on your path

oo = OCP();
oo.setServerLocation('http://openconnecto.me');
oo.setImageToken('kasthuri11cc');
oo.setAnnoToken('ac3ac4');
oo.setAnnoChannel('ac4_neuron_truth');

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% W Gray Roncal - 01.29.2015
% Server upload test - demonstrates server write timing test and dense uploading best practices

%% Get Data
% View data cuboid here (100 megavoxels)
% http://braingraph1dev.cs.jhu.edu/ocp/overlay/0.7/ac4/xy/1/4400,5424/5440,6464/1100/
% Careful to use an API version compatible with the server
ocp = OCP();
ocp.setServerLocation('http://braingraph1.cs.jhu.edu');
ocp.setImageToken('kasthuri11cc');

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% Connectomics Class Matlab Crash Course - Part 1
% WRGR, 01.15.2015

x = 4 %init a variable
x = 4; %with no output
x %view variable
x = 5 %now x is 5
clear x %delete x
x = [5 4 3 2] %make a vector
whos x %examine variable